A Constraint Satisfaction Approach to the Robust Spanning Tree Problem with Interval Data
Abstract
Robust optimization is one of the fundamental approaches to deal with uncertainty in combinatorial optimization. This paper considers the robust spanning tree problem with interval data, which arises in a variety of telecommunication applications. It proposes a constraint satisfaction approach using a combinatorial lower bound, a pruning component that removes infeasible and suboptimal edges, as well as a search strategy exploring the most uncertain edges first. The resulting algorithm is shown to produce very dramatic improvements over the mathematical programming approach of Yaman et al. and to enlarge considerably the class of problems amenable to effective solutions.
Cite
Text
Aron and Van Hentenryck. "A Constraint Satisfaction Approach to the Robust Spanning Tree Problem with Interval Data." Conference on Uncertainty in Artificial Intelligence, 2002.Markdown
[Aron and Van Hentenryck. "A Constraint Satisfaction Approach to the Robust Spanning Tree Problem with Interval Data." Conference on Uncertainty in Artificial Intelligence, 2002.](https://mlanthology.org/uai/2002/aron2002uai-constraint/)BibTeX
@inproceedings{aron2002uai-constraint,
title = {{A Constraint Satisfaction Approach to the Robust Spanning Tree Problem with Interval Data}},
author = {Aron, Ionut D. and Van Hentenryck, Pascal},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2002},
pages = {18-25},
url = {https://mlanthology.org/uai/2002/aron2002uai-constraint/}
}